Rapid in-field soil analysis of plant-available nutrients and pH for precision agriculture—a review

IF 5.4 2区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
Elena Najdenko, Frank Lorenz, Klaus Dittert, Hans-Werner Olfs
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Abstract

There are currently many in-field methods for estimating soil properties (e.g., pH, texture, total C, total N) available in precision agriculture, but each have their own level of suitability and only a few can be used for direct determination of plant-available nutrients. As promising approaches for reliable in-field use, this review provides an overview of electromagnetic, conductivity-based, and electrochemical techniques for estimating plant-available soil nutrients and pH. Soil spectroscopy, conductivity, and ion-specific electrodes have received the most attention in proximal soil sensing as basic tools for precision agriculture during the last two decades. Spectral soil sensors provide indication of plant-available nutrients and pH, and electrochemical sensors provide highly accurate nitrate and pH measurements. This is currently the best way to accurately measure plant-available phosphorus and potassium, followed by spectral analysis. For economic and practicability reasons, the combination of multi-sensor in-field methods and soil data fusion has proven highly successful for assessing the status of plant-available nutrients in soil for precision agriculture. Simultaneous operation of sensors can cause problems for example because of mutual influences of different signals (electrical or mechanical). Data management systems provide relatively fast availability of information for evaluation of soil properties and their distribution in the field. For rapid and broad adoption of in-field soil analyses in farming practice, in addition to accuracy of fertilizer recommendations, certification as an official soil analysis method is indispensable. This would strongly increase acceptance of this innovative technology by farmers.

用于精准农业的植物可利用养分和 pH 值田间土壤快速分析综述
目前,精准农业领域有许多估算土壤特性(如 pH 值、质地、总碳、总氮)的田间方法,但每种方法都有各自的适用性,只有少数几种方法可用于直接测定植物可利用的养分。作为有望在田间可靠使用的方法,本综述概述了用于估算植物可利用的土壤养分和 pH 值的电磁技术、基于电导率的技术和电化学技术。在过去二十年中,土壤光谱、电导率和离子特异性电极作为精准农业的基本工具,在近距离土壤传感领域受到了最广泛的关注。光谱土壤传感器可显示植物可利用的养分和 pH 值,电化学传感器可提供高精度的硝酸盐和 pH 值测量。这是目前精确测量植物可利用的磷和钾的最佳方法,其次是光谱分析。出于经济和实用性的考虑,多传感器田间方法与土壤数据融合的结合已被证明在评估土壤中植物可利用养分的状况以实现精准农业方面非常成功。传感器的同时运行可能会带来一些问题,例如不同信号(电子或机械信号)的相互影响。数据管理系统可以相对快速地提供用于评估土壤特性及其在田间分布的信息。要想在农业实践中快速、广泛地采用田间土壤分析方法,除了要保证肥料建议的准确性外,还必须获得官方土壤分析方法认证。这将大大提高农民对这一创新技术的接受程度。
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来源期刊
Precision Agriculture
Precision Agriculture 农林科学-农业综合
CiteScore
12.30
自引率
8.10%
发文量
103
审稿时长
>24 weeks
期刊介绍: Precision Agriculture promotes the most innovative results coming from the research in the field of precision agriculture. It provides an effective forum for disseminating original and fundamental research and experience in the rapidly advancing area of precision farming. There are many topics in the field of precision agriculture; therefore, the topics that are addressed include, but are not limited to: Natural Resources Variability: Soil and landscape variability, digital elevation models, soil mapping, geostatistics, geographic information systems, microclimate, weather forecasting, remote sensing, management units, scale, etc. Managing Variability: Sampling techniques, site-specific nutrient and crop protection chemical recommendation, crop quality, tillage, seed density, seed variety, yield mapping, remote sensing, record keeping systems, data interpretation and use, crops (corn, wheat, sugar beets, potatoes, peanut, cotton, vegetables, etc.), management scale, etc. Engineering Technology: Computers, positioning systems, DGPS, machinery, tillage, planting, nutrient and crop protection implements, manure, irrigation, fertigation, yield monitor and mapping, soil physical and chemical characteristic sensors, weed/pest mapping, etc. Profitability: MEY, net returns, BMPs, optimum recommendations, crop quality, technology cost, sustainability, social impacts, marketing, cooperatives, farm scale, crop type, etc. Environment: Nutrient, crop protection chemicals, sediments, leaching, runoff, practices, field, watershed, on/off farm, artificial drainage, ground water, surface water, etc. Technology Transfer: Skill needs, education, training, outreach, methods, surveys, agri-business, producers, distance education, Internet, simulations models, decision support systems, expert systems, on-farm experimentation, partnerships, quality of rural life, etc.
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